Abhijit Brahme

Determination of the Minimum Scan Size to Obtain Representative Textures by Electron Backscatter Diffraction

A new method for analyzing microstructure is proposed to evaluate the long-range dependence of texture. The proposed method calculates the average disorientation as a function of distance between data points as measured by electron backscatter diffraction patterns. This method gives a measure of clustering of texture and is used to evaluate accurately the effective grain size. This procedure in conjunction with Information theory is used to estimate a representative scan size for various materials. Analyses show that the optimal scan size depends on grain morphology and crystallographic texture. The results also indicate that on an average the optimal scan size needs to be 10 times the effective grain size.

Reconstruction of the 3D representative volume element from the generalized two-point correlation function

This paper presents the first application of three-dimensional (3D) cross-correlation microstructure reconstruction implemented for a representative volume element (RVE) to facilitate the microstructure engineering of materials. This has been accomplished by developing a new methodology for reconstructing 3D microstructure using experimental two-dimensional electron backscatter diffraction data. The proposed methodology is based on the analytical representation of the generalized form of the two-point correlation function—the distance-disorientation function (DDF). Microstructure reconstruction is accomplished by extending the simulated annealing techniques to perform three term reconstruction with a minimization of the DDF. The new 3D microstructure reconstruction algorithm is employed to determine the 3D RVE containing all of the relevant microstructure information for accurately computing the mechanical response of solids, especially when local microstructural variations influence the global response of the material as in the case of fracture initiation.

New Methodology to Determine Stable Texture Components under Cold Rolling in FCC Metals

In this work evolution of texture components during deformation of AA5754 aluminum alloy sheet under cold rolling is studied by analyzing the evolution of element-rotation-distribution calculated using a rate-dependent crystal plasticity finite element model (CPFEM). The proposed criteria can successfully predict the stability of a given textural component for cold rolling deformation in FCC materials with high stacking fault energy that deform predominantly by slip. Comparison of simulation results with experimental data shows that this approach successfully captures the stable textures reported for cold rolled AA5754 sheets. With the initial texture and the strain path, it is believed that, the method described in this work can be used to predict the final stable textures without any need for expensive crystal plasticity based numerical simulations and this could be of immense help for simulating large strain deformation of macroscale sheet samples exhibiting texture evolution.

Analytical estimation of distance–disorientation function of the material microstructure

Abstract This work presents a new functional approach to estimate the distance–disorientation correlation function of a given microstructure. The proposed approach separates the crystallographic domain into texture defined by its Euler angles ( ) and geometrical domain defined by distance distribution function . The crystallographic domain is treated as independent (known) variable and an analytical estimate for the Euclidian distance distribution function is obtained. The proposed analytical solution for the estimation of is based on existing statistical growth models and the logistic probability distribution function. The solution is optimized for the measured experimental data and takes into account morphological features of the microstructure such as grain volume, grain radius and grain size as well as their distribution inside the material. An analytical model is proposed for constructing the distance–disorientation function (DDF) using the estimated Euclidian distance between pixel pairs. The new functional solution is a highly effective way to calculate DDF values, making it suitable for application to the real microstructure optimization problems. The DDF obtained by using the results of probabilistic solution is validated by comparing them with the DDF obtained from experimental electron back-scatter diffraction data.

A Texture Component Model for Predicting Recrystallization Textures

The study presents an analytical model for predicting crystallographic textures and the final grain size during primary static recrystallization of metals using texture components. The kinetics is formulated as a tensorial variant of the Johnson-Mehl-Avrami-Kolmogorov (JMAK) equation. The tensor form is required since the kinetic and crystallographic evolution of the microstructure is described in terms of a limited set of growing (recrystallizing) and swept (deformed) texture components. The number of components required defines the order of the tensor since the kinetic coupling occurs between all recrystallizing and all deformed components. The new method is particularly developed for the fast and physically-based process simulation of recrystallization textures with respect to processing. The present paper introduces the method and applies it to the primary recrystallization of low carbon steels.

Determining a Stable Texture Condition Under Complex Strain Path Deformations in Face Centered Cubic Metals

Evolution of texture components during deformation of lightweight aluminum alloy sheet under different strain paths is studied by analyzing the evolution of element rotation calculated using a rate-dependent crystal plasticity finite element model. Based on a stability criteria proposed by Ali et al. (Light Metals 2016. Wiley, London, pp. 159–162, 2016), data from cold rolling, shear and compression simulations is analyzed to determine stable texture components. The predicted stable texture components, for the same microstructure, for rolling, shear and compression using the stability criteria are in-line with experimental observations. Further analysis of simulated data yields a simpler methodology that stable texture components are those that are aligned with the loading direction. Using this methodology, stable textures under rolling, shear and plane-strain compression are analytically identified and the results show an excellent conformity to experimental data. This new methodology can be included in robust non-texture based phenomenological modelling to predict texture evolution in engineering design problems.

Comparison of Localized Deformation in Crystal Plasticity Based Finite Element Simulations between Experimentally Measured and Statistically Generated Three-Dimensional Microstructures for the Aluminum Alloy 5754

This paper presents three dimensional (3D) grain structure of AA5754-O aluminum sheet collected by serial sectioning using a Dual Beam Focused Ion Beam equipped with Electron Backscatter Diffraction (EBSD) to enable an evaluation of the necessity for obtaining real 3D microstructures instead of generating 3D microstructures from 2D data using statistically equivalent microstructure generation techniques. A volume of 45.5x51x33μm material is sampled to construct the 3D microstructure and the corresponding equivalent 3D microstructure is generated using M-builder. These data sets are processed to build FE meshes containing real grain morphology and orientation. FE simulations of deformation fields using rate dependant crystal plasticity theory are conducted on both the real and generated microstructures and the predicted Forming Limit Diagrams (FLD’s) for the two microstructures are compared with the experimental FLD from the same alloy AA5754. Significant differences are observed between the two microstructures.